Helmholtz Center for Information Security
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Elektronischer Rechtsverkehr in Verfahren ohne Anwaltszwang - der Justizgewährungsanspruch des Bürgers als praktischer und theoretischer Störfaktor? - Anmerkungen insbesondere aus amtsrichterlicher Sicht
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Oblivion: Mitigating Privacy Leaks by Controlling the Discoverability of Online Information
No full textSearch engines are the prevalently used tools to collect information about individuals in the Internet. Search results typically comprise a variety of sources that contain personal information -- either intentionally released by the person herself or unintentionally leaked or unnoticedly published by third parties, often with detrimental effects on the individual's privacy. To grant individuals the ability to regain control over their disseminated personal information, the European Court of Justice recently ruled that EU citizens have a right to be forgotten in the sense that indexing systems, such as Google, must offer them technical means to request removal of links from search results that point to sources violating their data protection rights. As of now, these technical means consist of a web form that requires a user to manually identify all relevant links herself upfront and to insert them into the web form, followed by a manual evaluation by employees of the indexing system to assess if the request to remove those links is eligible and lawful.
In this work, we propose a universal framework Oblivion to support
the automation of the right to be forgotten in a scalable,
provable and privacy-preserving manner. First, Oblivion enables a
user to automatically find and tag her disseminated personal
information using Natural Language Processing (NLP) and image recognition techniques and
file a request in a privacy-preserving manner. Second, Oblivion
provides indexing systems with an automated and provable eligibility
mechanism, asserting that the author of a request is indeed affected
by an online resource. The automated eligibility proof ensures censorship-resistance so that only legitimately affected
individuals can request the removal of corresponding links from
search results. We have conducted comprehensive evaluations of Oblivion showing that the framework is capable of handling 278 removal requests per second on a standard notebook (2.5 GHz dual core), and is hence suitable for large-scale deployment
Privacy Preserving Payments in Credit Networks
No full textA credit network models trust between agents in a distributed environment and enables payments between arbitrary pairs of agents. With their flexible design and robustness against intrusion, credit networks form the basis of several Sybil-tolerant social networks, spam-resistant communication protocols, and payment systems. Existing systems, however, expose agents' trust links as well as the existence and volumes of payment transactions, which is considered sensitive information in social environments or in the financial world. This raises a challenging privacy concern, which has largely been ignored by the research on credit networks so far. This paper presents PrivPay, the first provably secure privacy-preserving payment protocol for credit networks. The distinguishing feature of PrivPay is the obliviousness of transactions, which entails strong privacy guarantees for the network links. PrivPay does not require any trusted third party, maintains a high accuracy of the transactions, and provides an economical solution to network service providers. It is also general-purpose and applicable to all credit network-based systems. We implemented PrivPay and demonstrated its practicality by privately emulating transactions performed in the Ripple payment system over a period of four months